Text Generation
MLX
Safetensors
qwen3_5
censored
osirisbrain
apple-silicon
qwen3.5
agi
conversational
8-bit precision
Instructions to use osirisbrain/OsirisCortex-v7c-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use osirisbrain/OsirisCortex-v7c-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("osirisbrain/OsirisCortex-v7c-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use osirisbrain/OsirisCortex-v7c-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7c-MLX"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "osirisbrain/OsirisCortex-v7c-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use osirisbrain/OsirisCortex-v7c-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7c-MLX"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default osirisbrain/OsirisCortex-v7c-MLX
Run Hermes
hermes
- MLX LM
How to use osirisbrain/OsirisCortex-v7c-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "osirisbrain/OsirisCortex-v7c-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "osirisbrain/OsirisCortex-v7c-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "osirisbrain/OsirisCortex-v7c-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }'
How to use from
PiConfigure the model in Pi
# Install Pi:
npm install -g @mariozechner/pi-coding-agent# Add to ~/.pi/agent/models.json:
{
"providers": {
"mlx-lm": {
"baseUrl": "http://localhost:8080/v1",
"api": "openai-completions",
"apiKey": "none",
"models": [
{
"id": "osirisbrain/OsirisCortex-v7c-MLX"
}
]
}
}
}Run Pi
# Start Pi in your project directory:
piQuick Links
OsirisCortex-v7c-MLX (Censored)
The Cortex v7c — Osiris's sovereign reasoning brain (censored variant). Standard safety guardrails intact. Runs natively on Apple Silicon via MLX Metal.
Architecture
- Base Model: Qwen3.5-9B (9 billion parameters)
- Modification: None — original base model with safety alignment preserved
- Format: MLX 8-bit quantized (Apple Silicon native)
- Size: ~10 GB
- Speed: ~60-80 tokens/sec on M2 Pro (MLX Metal)
- Quality: Near-lossless vs FP16 (~1-2% degradation)
Why 8-bit
- Spanish coherence: 4-bit quantization degrades non-English languages significantly
- Conversational quality: 8-bit produces more natural, coherent dialogue
- Safety: Standard Qwen3.5 alignment — no abliteration
Usage
from mlx_lm import load, generate
model, tokenizer = load("osirisbrain/OsirisCortex-v7c-MLX")
prompt = tokenizer.apply_chat_template(
[{"role": "user", "content": "¿Cómo estás?"}],
add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, max_tokens=2048)
Credits
Quantized by mlx-community. Original model: Qwen/Qwen3.5-9B by Alibaba. Sovereign rebrand by OsirisBrain.
- Downloads last month
- 5
Model size
3B params
Tensor type
BF16
·
U32 ·
F32 ·
Hardware compatibility
Log In to add your hardware
8-bit
Start the MLX server
# Install MLX LM: uv tool install mlx-lm# Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7c-MLX"